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[misc] upgrade format to py39 (#7256)

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This commit is contained in:
hoshi-hiyouga
2025-03-12 00:08:41 +08:00
committed by GitHub
parent 5995800bce
commit 264538cb26
113 changed files with 984 additions and 1407 deletions
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47
src/llamafactory/hparams/parser.py
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@@ -19,7 +19,7 @@ import json
import os
import sys
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
from typing import Any, Optional, Union
import torch
import transformers
@@ -47,17 +47,15 @@ check_dependencies()
_TRAIN_ARGS = [ModelArguments, DataArguments, TrainingArguments, FinetuningArguments, GeneratingArguments]
_TRAIN_CLS = Tuple[ModelArguments, DataArguments, TrainingArguments, FinetuningArguments, GeneratingArguments]
_TRAIN_CLS = tuple[ModelArguments, DataArguments, TrainingArguments, FinetuningArguments, GeneratingArguments]
_INFER_ARGS = [ModelArguments, DataArguments, FinetuningArguments, GeneratingArguments]
_INFER_CLS = Tuple[ModelArguments, DataArguments, FinetuningArguments, GeneratingArguments]
_INFER_CLS = tuple[ModelArguments, DataArguments, FinetuningArguments, GeneratingArguments]
_EVAL_ARGS = [ModelArguments, DataArguments, EvaluationArguments, FinetuningArguments]
_EVAL_CLS = Tuple[ModelArguments, DataArguments, EvaluationArguments, FinetuningArguments]
_EVAL_CLS = tuple[ModelArguments, DataArguments, EvaluationArguments, FinetuningArguments]
def read_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> Union[Dict[str, Any], List[str]]:
r"""
Gets arguments from the command line or a config file.
"""
def read_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> Union[dict[str, Any], list[str]]:
r"""Get arguments from the command line or a config file."""
if args is not None:
return args
@@ -70,8 +68,8 @@ def read_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> Union[
def _parse_args(
parser: "HfArgumentParser", args: Optional[Union[Dict[str, Any], List[str]]] = None, allow_extra_keys: bool = False
) -> Tuple[Any]:
parser: "HfArgumentParser", args: Optional[Union[dict[str, Any], list[str]]] = None, allow_extra_keys: bool = False
) -> tuple[Any]:
args = read_args(args)
if isinstance(args, dict):
return parser.parse_dict(args, allow_extra_keys=allow_extra_keys)
@@ -161,31 +159,31 @@ def _check_extra_dependencies(
check_version("rouge_chinese", mandatory=True)
def _parse_train_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _TRAIN_CLS:
def _parse_train_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _TRAIN_CLS:
parser = HfArgumentParser(_TRAIN_ARGS)
allow_extra_keys = is_env_enabled("ALLOW_EXTRA_ARGS")
return _parse_args(parser, args, allow_extra_keys=allow_extra_keys)
def _parse_infer_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _INFER_CLS:
def _parse_infer_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _INFER_CLS:
parser = HfArgumentParser(_INFER_ARGS)
allow_extra_keys = is_env_enabled("ALLOW_EXTRA_ARGS")
return _parse_args(parser, args, allow_extra_keys=allow_extra_keys)
def _parse_eval_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _EVAL_CLS:
def _parse_eval_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _EVAL_CLS:
parser = HfArgumentParser(_EVAL_ARGS)
allow_extra_keys = is_env_enabled("ALLOW_EXTRA_ARGS")
return _parse_args(parser, args, allow_extra_keys=allow_extra_keys)
def get_ray_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> RayArguments:
def get_ray_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> RayArguments:
parser = HfArgumentParser(RayArguments)
(ray_args,) = _parse_args(parser, args, allow_extra_keys=True)
return ray_args
def get_train_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _TRAIN_CLS:
def get_train_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _TRAIN_CLS:
model_args, data_args, training_args, finetuning_args, generating_args = _parse_train_args(args)
# Setup logging
@@ -364,9 +362,7 @@ def get_train_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _
and training_args.resume_from_checkpoint is not None
):
logger.warning_rank0(
"Add {} to `adapter_name_or_path` to resume training from checkpoint.".format(
training_args.resume_from_checkpoint
)
f"Add {training_args.resume_from_checkpoint} to `adapter_name_or_path` to resume training from checkpoint."
)
# Post-process model arguments
@@ -382,20 +378,17 @@ def get_train_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _
# Log on each process the small summary
logger.info(
"Process rank: {}, world size: {}, device: {}, distributed training: {}, compute dtype: {}".format(
training_args.process_index,
training_args.world_size,
training_args.device,
training_args.parallel_mode == ParallelMode.DISTRIBUTED,
str(model_args.compute_dtype),
)
f"Process rank: {training_args.process_index}, "
f"world size: {training_args.world_size}, device: {training_args.device}, "
f"distributed training: {training_args.parallel_mode == ParallelMode.DISTRIBUTED}, "
f"compute dtype: {str(model_args.compute_dtype)}"
)
transformers.set_seed(training_args.seed)
return model_args, data_args, training_args, finetuning_args, generating_args
def get_infer_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _INFER_CLS:
def get_infer_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _INFER_CLS:
model_args, data_args, finetuning_args, generating_args = _parse_infer_args(args)
_set_transformers_logging()
@@ -426,7 +419,7 @@ def get_infer_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _
return model_args, data_args, finetuning_args, generating_args
def get_eval_args(args: Optional[Union[Dict[str, Any], List[str]]] = None) -> _EVAL_CLS:
def get_eval_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _EVAL_CLS:
model_args, data_args, eval_args, finetuning_args = _parse_eval_args(args)
_set_transformers_logging()